Papers
Nonconvex Optimization for Regression with Fairness Constraints
Junpei Komiyama, Akiko Takeda, Junya Honda et al.
Non-linear motor control by local learning in spiking neural networks
Aditya Gilra, Wulfram Gerstner
Nonoverlap-Promoting Variable Selection
Pengtao Xie, Hongbao Zhang, Yichen Zhu et al.
Nonparametric Regression with Comparisons: Escaping the Curse of Dimensionality with Ordinal Information
Yichong Xu, Hariank Muthakana, Sivaraman Balakrishnan et al.
Nonparametric variable importance using an augmented neural network with multi-task learning
Jean Feng, Brian Williamson, Noah Simon et al.
Not All Samples Are Created Equal: Deep Learning with Importance Sampling
Angelos Katharopoulos, Francois Fleuret
Not to Cry Wolf: Distantly Supervised Multitask Learning in Critical Care
Patrick Schwab, Emanuela Keller, Carl Muroi et al.
Obfuscated Gradients Give a False Sense of Security: Circumventing Defenses to Adversarial Examples
Anish Athalye, Nicholas Carlini, David Wagner
oi-VAE: Output Interpretable VAEs for Nonlinear Group Factor Analysis
Samuel K. Ainsworth, Nicholas J. Foti, Adrian K. C. Lee et al.
On Acceleration with Noise-Corrupted Gradients
Michael Cohen, Jelena Diakonikolas, Lorenzo Orecchia
One-Shot Segmentation in Clutter
Claudio Michaelis, Matthias Bethge, Alexander Ecker
On Learning Sparsely Used Dictionaries from Incomplete Samples
Thanh Nguyen, Akshay Soni, Chinmay Hegde
Online Convolutional Sparse Coding with Sample-Dependent Dictionary
Yaqing Wang, Quanming Yao, James Tin-Yau Kwok et al.
Online Learning with Abstention
Corinna Cortes, Giulia DeSalvo, Claudio Gentile et al.
Online Linear Quadratic Control
Alon Cohen, Avinatan Hasidim, Tomer Koren et al.
On Matching Pursuit and Coordinate Descent
Francesco Locatello, Anant Raj, Sai Praneeth Karimireddy et al.
On Nesting Monte Carlo Estimators
Tom Rainforth, Rob Cornish, Hongseok Yang et al.
On the Generalization of Equivariance and Convolution in Neural Networks to the Action of Compact Groups
Risi Kondor, Shubhendu Trivedi
On the Implicit Bias of Dropout
Poorya Mianjy, Raman Arora, Rene Vidal
On the Limitations of First-Order Approximation in GAN Dynamics
Jerry Li, Aleksander Madry, John Peebles et al.
On the Optimization of Deep Networks: Implicit Acceleration by Overparameterization
Sanjeev Arora, Nadav Cohen, Elad Hazan
On the Relationship between Data Efficiency and Error for Uncertainty Sampling
Stephen Mussmann, Percy Liang
On the Spectrum of Random Features Maps of High Dimensional Data
Zhenyu Liao, Romain Couillet
On the Theory of Variance Reduction for Stochastic Gradient Monte Carlo
Niladri Chatterji, Nicolas Flammarion, Yian Ma et al.